Tyler Ludwig

Elected district attorneys (DAs) have wide discretion to raise or lower criminal conviction rates, yet the extent to which DAs’ politics shape their decision-making remains unclear. We evaluate the causal impact of DA partisan affiliation on conviction rates, sentencing outcomes, and recidivism. Using quasi-random variation in DA partisanship stemming from close elections, we find that the marginal Democratic DA is 24 percent more likely to dismiss criminal cases than Republican counterparts, and 15 percent less likely to incarcerate defendants. Strikingly, defendants in jurisdictions with Democratic DAs are no more likely to re-appear in a future criminal case, which is consistent with the notion that criminal convictions have limited deterrence effects. We find similar patterns using an alternative matching specification that captures the average effect of prosecutor partisanship. Our findings underscore the degree to which the punitiveness of the criminal justice system hinges on the partisanship of local district attorneys.

Most U.S. cities have defined-benefit pensions for their public workers, creating an obligation that exposes sponsoring cities to shortfall risk. Large funding gaps in recent years have required increased pension payments and generated fiscal stress for cities. To analyze the effect of this “pension pressure”, I assembled a novel dataset which captures the universe of cities and their pensions in California from 2003 to 2016. I focus on the changes in city unfunded liability contributions. These mandatory, externally determined payments are plausibly exogenous to cities’ year-to-year spending needs. Using a first differences empirical specification, I find that cities primarily reduce non-current expenses, specifically capital investment. I also show that cities cut payrolls and employment, with police employment declines specifically. Further, there are accompanying increases in crime rates. These estimates imply that pension pressure impairs local public service provision, with contributions displacing other spending.

Since late 2017, various states and local governments have instituted salary history bans. These salary history bans, as their name suggests, generally prevent employers from asking job applicants about their previous positions’ salaries, wages, or benefits. The purpose of this legislation is to reduce the long-term effects of early career wage discrimination, especially for women or members of minority groups. Yet, unintended consequences may undermine the stated goal and increase churn in the labor market. I intend to research how this public policy which limits businesses’ information on prospective employees alters labor market functioning.

Using the Children of Immigrants Longitudinal Study (CILS) and the New Immigrant Survey (NIS), this paper estimates the effect of immigrants’ English proficiency on the educational performance of their children as well as measures of parental involvement in school. Together, the data allow us to examine children ranging from preschool to high school age. Given the confounding factors associated with English knowledge, we employ an instrumental variables two-stage least squares strategy that exploits parents’ age at arrival and whether their country of origin is English speaking. For the younger cohort, which we access through the NIS sample, our results suggest that children of immigrant parents with higher English language ability score higher on reading assessments as well as some math-related assessments. For the older students, which we assess through the CILS sample, we see a positive effect on reading scores as a result of parental English proficiency. When examining parental involvement, we find that English proficiency results in a higher likelihood of being part of a parent-teacher organization as well as a higher probability of parent-teacher interaction. Our results are robust to various specifications and alternative instrumental variables.